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published online 12 December 2012Journal of Attention DisordersYahaira Iriarte, Unai Diaz-Orueta, Eduardo Cueto, Paula Irazustabarrena, Flavio Banterla and Gema Climent

Advanced Virtual Reality Tool for the Assessment of Attention: Normative Study in Spain−−AULA

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An adequate level of attention is essential for the correct performance of the rest of higher cognitive processes (Fuster, 2001; Posner & Petersen, 1990). It is well estab-lished that attention disturbance is the main symptom of some of the clinical syndromes such as the ADHD (Barkley, 1997; Cardo et al., 2011, Seidman, 2006). ADHD is mainly characterized by attentional lability, impulsive behavioral style, sterile hyperactivity, and frailty of the mechanisms of adaptation to the environment (Narbona, 2001; Narbona & Schulumberger, 2007; Seidman, 2006). It is one of the most common neurodevelopmental disorders in childhood (Cornelio-Nieto, Borbolla-Sala, & Gallegos-Dimas, 2011; Rodríguez et al., 2009; Rowland, Lesesne, & Abramowitz, 2002), and it implies relevant consequences for everyday life in individuals suffering from it as well as for their rela-tives. In a recent meta-analysis of more than 300 studies, most of them performed in the last 10 years, a worldwide prevalence of 5% in schoolchildren is estimated, and it is observed that, when using the same diagnostic criteria, such prevalence is similar in all studied countries (Polanczyk, Lima, Horta, Biederman, & Rohde, 2007).

Although there is controversy and it is not a requisite to formulate an ADHD diagnosis, there is wide consensus in considering neuropsychological evaluation as a very useful resource in the approach to this pathology due to the

following reasons (Barkley, 1994, 2006; Crespo-Eguilaz, Sánchez-Carpintero, & Narbona, 2010; Holmes et al., 2010; Quinlan, 2000; Soutullo & Diez Suárez, 2007):

• It adds value and accuracy to the traditional diag-nostic procedure for ADHD, often based heavily on symptoms assessed by behavioral checklists lacking diagnostic utility.

• It provides a better knowledge about the strat-egies and resources of the child with relation to tasks that put into practice attention and control of impulsive responses.

• It allows the identification of comorbid disorders and a more accurate diagnosis and therapeutic proposal.

• It specifies in an objective manner the changes produced after treatment as well as the develop-ment of the disorder.

465335 JADXXX10.1177/1087054712465335Journal of Attention DisordersIriarte et al.© 2012 SAGE Publications

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1Nesplora Technology & Behavior, Donostia-San Sebastian, Spain2Universidad de Oviedo, Spain

Corresponding Author:Yahaira Iriarte, Nesplora Technology & Behavior, Parque Tecnológico Miramón, Paseo Mikeletegi, 54, 20009 Donostia-San Sebastián, Spain Email: [email protected]

AULA—Advanced Virtual Reality Tool for the Assessment of Attention: Normative Study in Spain

Yahaira Iriarte1, Unai Diaz-Orueta1, Eduardo Cueto2, Paula Irazustabarrena1, Flavio Banterla1, and Gema Climent1

Abstract

Objective: The present study describes the obtention of normative data for the AULA test, a virtual reality tool designed to evaluate attention problems, especially in children and adolescents. Method: The normative sample comprised 1,272 participants (48.2% female) with an age range from 6 to 16 years (M = 10.25, SD = 2.83). The AULA test administered to them shows both visual and auditory stimuli, while randomized distractors of ecological nature appear progressively. Results: Variables provided by AULA were clustered in different categories for their posterior analysis. Differences by age and gender were analyzed, resulting in 14 groups, 7 per sex group. Differences between visual and auditory attention were also obtained. Conclusion: Obtained normative data are relevant for the use of AULA for evaluating attention in Spanish children and adolescents in a more ecological way. Further studies will be needed to determine sensitivity and specificity of AULA to measure attention in different clinical populations. (J. of Att. Dis. 2012; XX(X) 1-XX)

Keywords

attention, ADHD, AULA, virtual reality, normative data



2 Journal of Attention Disorders XX(X)

• It can sometimes provide alternative explanations to the symptoms (Barkley, 2006), providing highly recommendable cognitive profiles.

• It is useful to relate IQ to attentional abilities. • It provides information that cannot be obtained in

any other way (Quinlan, 2000).

When it comes to consider different neuropsychological assessment tools for the assessment of ADHD, there are some tests that only attend to one sensorial modality. This is the case of Conners’ Continuous Performance Test (CPT; Conners, 1994a, 1994b), the Children Sustained Attention Task (CSAT) by Servera and Llabrés (2004), or the DiViSA-UAM (Test de Discriminación Simple de Árboles-Universidad Autónoma de Madrid [Simple Tree Discrimination Test-Autonomous University of Madrid]) and TACI-UAM (Test de Aprendizaje de Categorías-Inhibición-Universidad Autónoma de Madrid [Category Learning-Inhibition Test-Autonomous University of Madrid]; Quiroga, Santacreu, Montoro, Martínez-Molina, & Chun, 2011). For those which integrate both sensorial modalities, visual and auditory, they may lack ecological valid-ity, as it happens with Integrated Visual and Auditory (IVA) CPT (Tinius, 2003) or Test of Variables of Attention (TOVA) CPT (Leark, Greenberg, Kindschi, Dupuy, & Hughes, 2007). Other possible limitations of all the tests mentioned above are that they include neither distractors (although their influence in ADHD children have already been documented, as in Xu, Zhou, & Wang, 2004) nor head motor activity (i.e., both irrel-evant and relevant movements of the head—that is, relevant to the performance of attending the task) and are usually admin-istered in an evaluation context that lacks ecological validity (i.e., the evaluation context differs in many ways from the real-life environment where the child may experience his or her attentional problems).

Currently, new technological developments in the field of virtual reality (VR) offer novel and interesting options in the neuropsychological evaluation of many cognitive pro-cesses. VR reproduces three-dimensional (3D) environ-ments in which the examined person interacts in a dynamic way, with a sense of immersion in that environment similar to the presence and exposure to a real environment (Climent, Banterla, & Iriarte, 2010). Diverse studies have shown the practical utility of VR in the health care environment, in different domains such as rehabilitation of cerebral palsy (Huber et al., 2010), pain treatment or distraction (Das, Grimmer, Sparnon, McRae, & Thomas, 2005; Rutter, Dahlquist, & Weiss, 2009), or identification and treatment of older people with cognitive disorders (Cherniack, 2011), although the scientific evidence of its utility is still limited, and further research and studies are required. Interestingly, lately VR has been considered a reliable method to test ADHD children’s ability to sustain performances over time, especially by the research team of Rizzo (Bioulac et al., 2012; Rizzo et al., 2006; Rizzo et al., 2000).

In relation to this, the aim of this study was to obtain normative data for the AULA VR test on a Spanish popula-tion of children between 6 and 16 years old. AULA is a VR test designed to evaluate attention problems, especially in children and adolescents, and help the clinicians in comple-menting the information included in the diagnosis and sub-sequent follow-up of ADHD. It is not that neuropsychological evaluation is a requisite for ADHD diagnosis, but different authors have described the use of this type of evaluations as an interesting complement for the understanding of the dis-ease, as it has been already stated above. In comparison with other classical tests, AULA shows the novelty of being presented as a VR “game,” thus facilitating the initial pre-disposal of children and adolescents to the evaluation. This does not mean that the test is funny for them (on the con-trary, many complained about being “too tough”), but it appeared a priori as more attractive for them than traditional which paper-and-pencil tests.

MethodParticipants

The normative sample was composed of 1,272 participants (all of them Caucasian, 48.2% female) with an age range from 6 to 16 years old (M = 10.25, SD = 2.83). All of them had Spanish as their mother tongue. This was the final sample after the exclusion of 10 participants (4 cases who were younger than 6 and 6 cases older than 16). As it was considered that these participants may have biased the results of their corresponding age group, it was decided to exclude them from the normative group. Figure 1 shows the distribution by age and sex in the normative group.

Assuming an estimation of 20% of participants who might have dropped from the study and the need to obtain a minimum sample of 800 children to fulfill the goal of obtaining normative data for the test, it was decided to approach a range of 1,000 to 1,500 children aged from 6 to 16 years. Previously, to facilitate participants’ participation, informed signed consent forms from the parents and from the children themselves (if they were older than 12 years) were obtained. Personal sensitive data were anonymized from the rest of the data used and analyzed in the study. The only personal data used in the subsequent analyses were basic sociodemographical data (sex and age). The recruit-ment was performed in four different schools from the regions of Basque Country and Navarra in northern Spain. The sample was incidental, and depending on their willing-ness to participate in the experiment, schools were selected and individual potential participants were contacted (always trying to guarantee the minimum amount of users necessary for a valid sample size). At the same time, all the school-children from 6 to 16 years old had full freedom to partici-pate or not in the study, and every student fulfilling the age



Iriarte et al. 3

range inclusion criteria had the same chance to be included in the study. Finally, students from four schools of the urban area participated in the study. No specific evaluations were previously performed to exclude children with potential psychiatric disorders or other neurodevelopmental disor-ders. It was decided that, to guarantee a recruitment as rep-resentative as possible from the general population, no disorder-specific exclusion criteria would be set; in this way, it is assumed that the potential prevalence of children suffering from any kind of psychiatric or neurodevelop-mental disorder in the normative sample will be a percent-age equal or at least very close to the prevalence in the general population. Only children with visual or auditory disorders as to make them unable to take the AULA test were excluded from the normative sample.

MeasureAULA was developed with the goal of being used as an aid to the clinician in the diagnosis of ADHD. In this sense, the model of attention on the basis of its development is Sergeant et al.’s state regulation model (Sergeant, Oosterlaan, & Van der Meere, 1999), which proposes that, to reach any goal, activation and mobilization of mental energy is required to adapt cognitive energies to external demands and thus optimize the answer. It is a similar con-cept to mental effort or motivation. State regulation can be considered an executive function, dependent on frontal lobe and its connection with the limbic system. This hypothesis, as well as Barkley’s unique deficit model, accepts execu-tive dysfunction as a nuclear aspect of ADHD. In comput-

erized neuropsychological tools, state regulation deficit is observed in the disruption of reaction time, because of slowness and lack of regularity, and the basic neuropsycho-logical paradigm of basic deficit is expressed in go/no go type of tasks. Fast presentation of stimuli induces an over-stimulation that derives in fast, imprecise and inadequate answers; on the contrary, slow presentation of stimuli induces a hypoactivation and, as a consequence, slow, vari-able and inefficient answers. It shows a low ability to gen-erate the necessary energy adjustment to answer to environmental demands. The relationship between ADHD symptoms and variability in reaction time (RT) has been shown in clinical samples (Johnson et al., 2007) as in popu-lation samples (Berwid, Curko Kera, Marks, Santra, & Bender, 2005).

ProcedureThe test administration and collection of normative data were performed by expert evaluators, psychologists, and psychopedagogists of Nesplora and undergraduate students of the latest years of psychology of local universities, prop-erly trained on the standardized procedures for the admin-istration of the AULA test.

AULA is based on the paradigm of other CPTs but per-formed in a VR environment, and it is visualized by means of a special set of VR glasses with movement sensors. The scenario is similar to either a primary or a high school class-room, and the perspective (i.e., what the participant sees) is placed in one of the classroom desks, looking to the black-board. AULA is composed by two main exercises: (a) a

Figure 1. Normative sample distribution by age and sex (N = 1,272)




No-X-paradigm-based exercise (i.e., press the button when you do not see or hear “apple”) and (b) an X-paradigm-based exercise (i.e., press the button whenever you do see or hear “seven”). The reason for this sequence of presentation (i.e., first No-X, then X) is that No-X tasks generate an overstimulation that derives in fast, inaccurate and inade-quate responses, whereas X tasks lead to a hypoactivation and thus to slow, variable and inefficient answers (Artigas-Pallarés, 2009). It is assumed that this sequence of presenta-tion reproduces more accurately the problem faced by a child with self-regulation problems (as it happens in chil-dren with attentional problems) to adapt to new environ-mental requirements once he or she has performed an overstimulating activity, as it is stated by the model of state regulation by Sergeant et al. (1999).

Stimuli are presented both on a visual and auditory basis, and at the same time, previously randomized distractors of ecological nature (i.e., equal to those that may appear in a real classroom environment, such as the teacher walking through the room, object drop-off, environmental noises, etc.) appear progressively. Table 1 shows an overview of presented visual and auditory stimuli.

Distractors are both visual and auditory, and may at times appear combined in both sensorial modalities. Special attention was paid, especially with younger kids, in show-ing them the different technological components (VR glasses, switches, audio headset, etc.) to minimize anxiety associated with the evaluation context.

Previous to the administration of the test, and to familiar-ize each participant with the technology of AULA, partici-pants were asked about their experience with computers, knowledge about VR, videogames, and so on. Any clues or information about the contents of the test were avoided to prevent administration biases.

Once the participant was equipped with the technologi-cal devices needed to perform AULA, the test started with

an audio displaying basic instructions: “Hello, welcome to AULA, with the glasses you are wearing you can see the whole classroom, at your left, right, up and down . . . you can see everything” followed by the description of the classroom environment and the type of stimuli and tasks that are going to be presented. Figure 2 provides a fast view of the evaluation setting in AULA, whereas Figure 3 shows an image of how AULA test looks like once the user puts the VR glasses on.

The first tasks of the administration were brief training tasks, with two purposes: (a) have the participants familiar-ized with the type of tasks they will have to perform subse-quently and (b) avoid a state of overmotivation (or, on the contrary, anxiety) in children due to the excitement pro-voked by the use of this type of novel technologies.

Evaluation by means of AULA allows the analysis of the behavior and information processing skills of the child in both X and No-X tasks (including impulsive behavior), both with and without distractors, and this is examined with values associated with each of the distractors. In addition, the information obtained allows establishing differences

Table 1. Visual and Auditory Stimuli in AULA

Auditory Visual Auditory Visual

1 Árbol (tree) Cinco (five)

2 Botella (bottle) Seis (six)

3 Libro (book) Siete (seven)

4 Manzana (apple) Ocho (eight)

5 Tarta (cake) Nueve (nine)

Siervo* — Siembro* —

Note: *Distractor in Spanish for the word siete (seven).

Figure 2. AULA test evaluation setting

Figure 3. AULA test running



Iriarte et al. 5

between visual and auditory processing skills. Finally, motor performance during the task and attentional focus shifting are analyzed. The complete administration of AULA lasts approximately 20 min.

After each administration of AULA, the character of the teacher himself, the one that is displayed in the virtual class-room, told the child to remove the VR glasses. The evalua-tor helped, when necessary, the participant remove the glasses, and informal questions about the user’s experience with the test were asked.

Below, we present a description of the different mea-sures obtained with AULA:

• Omission errors: This type of errors is related to inattention and occurs when the child does not press the button when he should have to—that is, when the target stimulus appears. This implies that a person who obtains several omission errors can be sensitive either to monotony, thus lacking good attention capabilities, or to problems in the man-agement of information processing from two dif-ferent sensorial modalities. This measure is related to selective and focalized attention. In AULA, these type of errors can be considered as a general measure or can further be categorized by the sen-sorial modality of the overlooked stimulus (visual omissions vs. auditory omissions), by the influ-ence of distractors (omissions with distractors vs. omissions without distractors), or by the type of task (No-X task omissions vs. X task omissions).

• Commission errors: There is agreement that this type of error represents impulsivity and occurs when the child presses the button when he should not have to—that is, when the target stimulus has not appeared yet. This implies that a person with several commission errors has a low capacity to control his answer or is too impulsive. This mea-sure is related to lack of motor control or lack of inhibition of response. In AULA, these type of errors can be considered as a general measure or can further be categorized by the sensorial modal-ity of the anticipated stimulus (visual commissions vs. auditory commissions), by the influence of distractors (commissions with distractors vs. com-missions without distractors), or by the type of task (No-X task commissions vs. X task commissions).

• Reaction time: This is the time required to answer a stimulus. It tends to be longer in people with atten-tion deficit because they tend to process the informa-tion slower (Parsons, Bowerly, Buckwalter, & Rizzo, 2007; Rizzo et al., 2006). AULA collects this mean value (M and SD) in different stages: tasks with dis-tractors, tasks without distractors, No-X task, X task, auditory stimuli, visual stimuli, and so on to observe

qualitative differences in the child’s performance. In addition, reaction times are measured not only when correct answers are provided but also when com-mission errors take place (i.e., the child is told not to press when X stimulus appears, but he or she finally presses it, and the lapse between the presentation of the stimulus and the presentation of the answer—commission error—is registered).

• Motor activity: Due to the movement sensors placed in the VR headset, movements of user’s head are captured, to register frequency and rel-evance (i.e., necessary vs. unnecessary move-ments). We can also measure distance to the attention focus or how much and when the child deviates this head from the target stimulus.

• Differentiation between No-X and X tasks: No-X tasks contain several stimuli and may induce an overstimulation that challenges the individual’s skills to control his or her impulses; however, X task is slower and more monotonous, thus leading to a hypoactivation that makes it difficult to sus-tain attention and/or concentration.

• Comparison of sensorial modalities: Comparison of users’ answers to visual and auditory stimuli provides information about divided attention.

• Quality of attention focus: It provides information on whether the quality of user’s performance is differ-ent due to either internal or external stimuli, when the target stimuli are present and the user is paying attention to the classroom blackboard. It is obtained scoring the amount of visual omission and commis-sion errors performed by the participant when he or she has the blackboard in his or her viewing angle.

ResultsTo provide a clarifying explanation about the extensive amounts of results provided by AULA, we have clustered the variables in some specific categories, and for each of these categories, we present the raw scores for the norma-tive groups obtained (divided by age and sex):

• Visual attention: It comprises total visual omission errors, visual commission errors, as well as reaction time (measured in milliseconds) for both visual cor-rect answers and visual commission errors. Tables 2 and 3 provide an overview of normative raw data (Ms and SDs) for the normative groups obtained.

• Auditory attention: It comprises total auditory omis-sion errors, auditory commission errors, as well as reaction time (measured in milliseconds) for both auditory correct answers and auditory commission errors. Tables 4 and 5 provide raw data for the nor-mative groups obtained divided by age and sex.




Table 2. Visual Attention (6-11-Year-Old Groups)

6 years old 7 years old

Boys (n = 78) Girls (n = 60) Boys (n = 90) Girls (n = 60)

M SD M SD M SD M SD

Visual omission errors 40.92 25.91 41.70 24.99 33.93 24.38 28.55 20.09Visual commission errors 11.22 10.23 8.08 10.51 8.82 6.57 8.88 5.81RT visual correct answers 875.01 246.25 943.16 201.45 810.69 165.72 828.69 132.04RT visual commission errors 776.68 345.94 845.05 394.22 670.06 260.42 746.39 250.76



M SD M SD M SD M SD




M SD M SD M SD M SD


Table 3. Visual Attention (12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Visual omission errors

8.70 13.76 6.88 10.55

Visual commission errors

7.91 9.22 7.22 10.65

RT visual correct answers

606.92 103.04 614.82 99.18

RT visual commission errors

515.29 187.23 506.69 221.36

• Performance under the influence of distractors: This category addresses specifically the performance of the children in the presence of both visual and auditory distractors. It includes both omission and commission errors executed when distractors are present, reaction time (in milliseconds) for correct answers and commission errors, as well as motor

activity and deviation from the focus (i.e., time when the child is not looking at the blackboard, measured in milliseconds) when distractors are present. Tables 6 and 7 show the raw data for the normative groups obtained.

• Performance in the absence of distractors: It provides the same measures as above but only referred to the test administration sequences when distractors are absent (omission and commission errors without distractors, reaction time for cor-rect answers and commission errors without dis-tractors, and motor activity and deviation from the focus when distractors are not present). Tables 8 and 9 show the raw data for the normative groups obtained.

• No-X-task-specific performance (impulsivity): According to Sergeant’s and Barkley’s model, a No-X-paradigm-based task will provide a mea-sure on impulsivity, especially useful in measur-ing not only attentional processes but also as an aid in the diagnosis of potential conditions com-prising impulsivity such as ADHD disorder. Thus, this category comprises, only for the sequence in which No-X task is presented (i.e., press the



Iriarte et al. 7

X-paradigm-based task will provide a measure on inattention, especially useful in measuring not only attentional processes but also as an aid in the diagnosis of potential conditions compris-ing impulsivity such as ADHD disorder. The same measures as above are comprised in this category, which is specific for children’s answers during the sequence where the X task is presented (i.e., press whenever you listen or see the target stimulus). Tables 12 and 13 show the raw data for the norma-tive groups obtained.

• Total scores: Finally, total scores were obtained as a measure of children’s overall performance. This category includes total commission errors, total omission errors, total motor activity, total deviation from the focus, and reaction times for both general correct answers and total commission errors. Tables 14 and 15 show the raw data for the normative groups obtained.

Below, we present the results for statistical analyses per-formed, from which we justify the conformation of the 14 normative groups presented above, 7 per sex and 7 per age (one group per age from 6 to 11 years old and one composite group for children from 12 to 16 years old). Once confirmed that normality and homoscedasticity tests did not support a

Table 4. Auditory Attention (6-11-Year-Old Groups)



M SD M SD M SD M SD

Auditory omission errors 16.52 20.97 15.07 19.15 8.93 13.54 7.73 8.32Auditory commission errors 10.09 11.70 8.05 10.49 7.42 5.37 7.30 6.67RT auditory correct answers 1,148.73 168.35 1,187.89 156.74 1,084.98 200.56 1,119.84 127.76RT auditory commission errors 1,155.11 403.53 1,170.32 400.77 1,126.26 352.33 1,172.54 449.1



M SD M SD M SD M SD

Auditory omission errors 7.67 10.68 7.00 7.11 6.55 10.84 6.99 10.97Auditory commission errors 8.25 8.48 7.58 10.27 7.68 11.15 5.06 3.71RT auditory correct answers 1,037.57 133.61 1,108.52 139.76 1,041.48 141.84 1,096.75 146.11RT auditory commission errors 1,060.20 303.68 1,140.28 423.99 1,087.22 355.22 1,105.49 420.96



M SD M SD M SD M SD

Auditory omission errors 6.53 9.91 8.79 17.87 6.73 12.20 3.18 5.48Auditory commission errors 5.22 3.89 3.06 2.91 8.17 13.96 3.47 2.93RT auditory correct answers 1,055.73 208.28 1,073.02 124.95 1,020.99 124.97 1,005.10 113.71RT auditory commission errors 1,077.63 381.30 1,123.63 559.01 1,145.21 385.76 981.60 382.35

Table 5. Auditory Attention (12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Auditory omission errors

4.39 8.26 3.32 5.78

Auditory commission errors

4.26 8.49 4.57 10.83

RT auditory correct answers

988.24 142.37 969.11 133.32

RT auditory commission errors

969.09 483.04 956.36 459.56

button whenever you listen or see a stimulus that is not the target stimulus), omission and com-mission errors, reaction time for both correct answers and commission errors, motor activity, deviation from the focus, and blackboard errors. Tables 10 and 11 show the raw data for the nor-mative groups obtained.

• X-task-specific performance (inattention): Accord-ing to Sergeant’s and Barkley’s models, an




Table 6. Performance Under the Influence of Distractors (6-11-Year-Old Groups)



M SD M SD M SD M SD

Omission errors with distractors 20.68 13.20 20.00 11.84 15.56 10.04 13.73 7.99Commission errors with distractors 6.86 6.06 4.67 5.47 5.69 3.99 5.37 4.31RT correct answers with distractors 994.87 213.89 1,104.96 180.35 970.97 191.76 1,000.69 135.52RT commission errors with

distractors933.01 377.93 991.04 519.92 937.13 392.03 1,001.56 375.91

Motor activity with distractors 1.20 0.84 0.78 0.52 0.91 0.64 0.74 0.55Deviation from the focus with

distractors40,882.36 63,106.22 47,773.58 129,091.16 281,64.76 56,346.41 28,210.72 63,060.15



M SD M SD M SD M SD

Omission errors with distractors 11.63 9.33 10.48 8.21 9.94 8.86 8.86 8.96Commission errors with distractors 7.20 5.71 6.49 6.40 7.35 5.99 5.00 3.13RT correct answers with distractors 913.11 129.88 975.27 153.15 893.22 136.58 934.95 154.87RT commission errors with

distractors853.07 296.13 905.95 422.30 844.49 275.66 844.64 352.45


distractors23,004.45 45,335.13 10,712.22 34,117.46 10,574.48 27,754.48 7,328.29 22,981.72



M SD M SD M SD M SD

Omission errors with distractors 8.06 8.04 8.84 12.08 7.88 9.01 6.24 8.16Commission errors with distractors 6.02 3.52 3.97 2.51 6.94 7.94 4.20 2.74RT correct answers with distractors 889.56 228.18 894.14 124.44 853.06 116.14 854.20 122.91RT commission errors with

distractors776.98 286.96 849.60 445.96 833.14 296.72 775.84 348.10


distractors6,612.55 16,798.07 8,096.06 41,072.48 7,559.55 18,650.72 6,819.22 35,827.56

Table 7. Performance Under the Influence of Distractors (12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Omission errors with distractors

5.20 7.93 4.09 5.76

Commission errors with distractors

4.86 5.01 4.59 5.88

RT correct answers with distractors

812.58 130.32 808.77 126.53

RT commission errors with distractors

641.12 318.17 642.05 361.72

Motor activity with distractors

0.50 0.42 0.37 0.24

Deviation from the focus with distractors

7,282.71 29,550.72 3,650.77 18,398.77

normal distribution for most of the variables, nonparametric statistical analyses were performed. Subsequently, we pres-ent differences by sex, age, evolutive changes from 6 to 16 years old, and differences by sex within each age group. Finally, we present differences between visual and auditory attention for the total sample.

Overall Gender DifferencesInitially, the total sample was divided by sex (659 boys and 613 girls), and a Mann–Whitney U test was run to examine differences between the two resulting groups. Table 16 shows a general pattern of a significant worse performance in boys versus girls, as they execute more omission and commission errors of all types (visual, auditory, with and without distractors, as well as task specific—X, No-X). Motor activity and deviation from the focus are also



Iriarte et al. 9

Table 8. Performance in Absence of Distractors (6-11-Year-Old Groups)



M SD M SD M SD M SD

Omission errors without distractors 37.88 27.03 36.77 26.45 27.31 22.05 22.55 15.99Commission errors without distractors 16.03 16.46 11.47 15.48 10.56 7.47 10.82 8.51RT correct answers without distractors 1,024.37 176.86 1,074.56 140.91 963.47 178.66 982.54 112.29RT commission errors without

distractors973.20 299.85 993.15 355.28 871.04 294.9 898.58 344.87

Motor activity without distractors 1.34 0.86 0.87 0.62 0.97 0.64 0.83 0.62Deviation from the focus without

distractors47,600.95 63,164.64 54,423.95 145,517.57 27,150.60 51,781.49 22,096.02 38,524.81



M SD M SD M SD M SD

Omission errors without distractors 18.31 18.11 17.00 16.24 15.39 15.91 14.10 15.99Commission errors without distractors 12.69 11.16 11.75 15.67 12.17 17.61 8.17 5.18RT correct answers without distractors 892.15 131.22 934.90 113.86 867.20 110.07 899.29 118.66RT commission errors without

distractors786.67 248.44 877.42 293.28 756.39 187.43 799.12 295.56


distractors21,079.71 41,916.47 9,101.71 27,100.84 8,733.78 21,989.49 7,869.56 21,786.53



M SD M SD M SD M SD

Omission errors without distractors 10.83 11.22 13.15 20.78 11.67 14.55 9.69 13.77Commission errors without distractors 9.28 5.11 5.52 3.53 13.88 22.56 5.39 3.59RT correct answers without distractors 836.94 100.01 859.15 97.89 808.94 99.62 821.62 104.07RT commission errors without

distractors753.60 230.14 740.40 263.72 788.64 269.62 672.69 286.04


distractors5,074.30 10,789.76 3,528.61 14,987.98 4,988.09 13,338.92 4,049.94 13,527.97

Table 9. Performance in Absence of Distractors (12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Omission errors without distractors

7.88 11.85 6.10 9.59

Commission errors without distractors

7.31 12.89 7.20 15.78

RT correct answers without distractors

785.05 106.63 776.14 105.03

RT commission errors without distractors

692.06 266.95 682.27 306.36

Motor activity without distractors

0.50 0.37 0.37 0.22

Deviation from the focus without distractors

5,328.66 25,388.42 1,553.59 7,762.56

significantly worse for boys in most of the defined variable clusters. With regard to blackboard errors (a composite of omission and commission errors that occur when the child is looking at the blackboard), the performance in boys is worse for both No-X and X tasks. Finally, no statistically significant differences appeared for reaction times mea-sured, except for correct answers in No-X task, which was the only measure in which boys showed a better perfor-mance by means of providing faster correct answers.

Differences by AgeFirst, Kruskal–Wallis test was performed to explore gen-eral differences by age within boys from 6 to 16 years old and girls from 6 to 16 years old. In both cases, statisti-cally significant differences were obtained for absolutely




Table 10. No-X-Task-Specific Performance (Impulsivity, 6-11-Year-Old Groups)



M SD M SD M SD M SD

Omission errors (No-X) 48.28 35.94 47.33 33.49 35.59 26.54 30.33 20.64Commission errors (No-X) 11.40 7.19 8.57 6.36 10.99 5.89 11.55 6.55RT correct answers (No-X) 954.69 279.45 1,066.15 156.80 944.72 190.41 965.80 118.61RT commission errors (No-X) 939.30 374.39 973.81 393.59 902.29 305.99 939.48 307.76Motor activity (No-X) 1.04 0.72 0.72 0.54 0.81 0.66 0.67 0.50Deviation from the focus (No-X) 21,646.47 34,559.44 24,934.20 64,399.70 16,008.03 41,539.42 13,150.48 24,619.66Blackboard errors (No-X) 39.00 19.36 38.13 20.63 33.71 18.48 30.40 15.54



M SD M SD M SD M SD

Omission errors (No-X) 24.53 23.66 22.00 20.57 20.99 22.31 18.90 22.29Commission errors (No-X) 12.53 6.37 10.87 5.74 12.14 5.24 10.06 5.11RT correct answers (No-X) 879.19 123.51 938.85 141.86 856.86 130.94 903.84 135.80RT commission errors (No-X) 777.61 225.07 878.34 271.07 766.42 211.32 810.40 239.81Motor activity (No-X) 0.78 0.69 0.47 0.33 0.62 0.36 0.52 0.36Deviation from the focus (No-X) 9,193.10 22,529.77 2,315.36 6,189.40 5,283.48 10,577.54 4,343.97 13,441.85Blackboard errors (No-X) 26.02 17.18 23.65 16.94 23.43 15.86 19.56 13.98



M SD M SD M SD M SD

Omission errors (No-X) 15.73 17.74 19.64 30.46 15.86 20.93 13.96 20.65Commission errors (No-X) 12.00 5.68 7.52 3.98 10.48 5.39 8.10 4.92RT correct answers (No-X) 844.32 161.68 866.25 111.24 818.81 112.74 826.06 116.58RT commission errors (No-X) 724.41 186.85 747.92 243.47 768.67 240.44 715.49 262.67Motor activity (No-X) 0.52 0.28 0.42 0.41 0.49 0.30 0.36 0.29Deviation from the focus (No-X) 3,576.75 10,172.11 2,165.60 12,895.11 2,871.18 8,314.57 3,053.24 14,125.52Blackboard errors (No-X) 18.36 10.90 17.21 15.18 17.71 15.32 16.47 16.73

Table 11. No-X-Task-Specific Performance (Impulsivity, 12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Omission errors (No-X) 10.70 17.79 8.11 13.33Commission errors (No-X) 8.49 4.59 7.32 4.46RT correct answers (No-X) 788.09 123.29 782.91 116.34RT commission errors

(No-X)664.54 226.10 660.18 237.82

Motor activity (No-X) 0.44 0.33 0.32 0.19Deviation from the focus

(No-X)2,356.64 12,253.84 780.07 4,695.91

Blackboard errors (No-X) 13.22 12.59 10.64 10.04

all measures (all p < .001). Once the presence of statisti-cal differences by age was confirmed, a 2 × 2 post hoc study was performed to analyze which specific age groups were the ones that showed statistically significant differences.

Regarding visual attention, visual omission errors signifi-cantly decrease from 6 (m = 160.57) to 7 years old (m = 129.71; U = 8,132, p < .01), from 7 (m = 153.88) to 8 years old (m = 112.53; U = 6,243, p < .001), and from 9 (m = 148.80) to 10 years old (m = 123.26; U = 7,501.50, p < .01), whereas it is close but not within statistical significance from 11 to 12 years old (p = .081), always in a decreasing progression, showing that omission errors tend to decrease with age. Other scores showing improvements with age are average reaction time needed to provide correct answers,



Iriarte et al. 11

which shows significant differences from 6 to 7, 7 to 8, 9 to 10, and close to statistical significance from 11 to 12 (p = .070), showing no further significant differences between 12 and 16 years old. Finally, reaction time when performing commission errors also shows a decrease with age from 6 (m = 158.71) to 7 years old (m = 131.42; U = 8,388.5, p < .01), from 9 (m = 146.26) to 10 years old (m = 126; U = 7,860, p < .05), and from 10 (m = 133.05) to 11 years old (m = 114.93; U = 6,543.5, p < .05), showing no further sig-nificant differences between the rest of the age groups. These results indicate a relative age-dependent worsening in com-mission errors, as these types of errors appear to be faster when the children are progressively older, although commis-sion error rates do not significantly change with age. Table 17 summarizes these changes in a fast overview.

Table 12. X-Task-Specific Performance (Inattention, 6-11-Year-Old Groups)



M SD M SD M SD M SD

Omission errors (X) 10.28 6.69 9.43 6.75 7.28 6.84 5.95 5.42Commission errors (X) 11.49 18.39 7.57 17.19 5.26 6.60 4.63 6.81RT correct answers (X) 1,132.16 179.22 1,156.45 163.08 1,051.43 177.42 1,083.62 150.86RT commission errors (X) 974.22 423.89 929.31 576.05 830.73 483.44 941.52 572.39Motor activity (X) 1.39 0.95 0.87 0.62 0.99 0.65 0.84 0.68Deviation from the focus (X) 27,868.06 35,768.94 31,120.77 81,724.16 13,679.94 22,919.67 10,357.50 19,115.82Blackboard errors (X) 11.19 8.84 9.75 9.68 7.58 6.38 6.18 5.72



M SD M SD M SD M SD

Omission errors (X) 5.41 4.80 5.48 5.26 4.35 4.32 4.06 4.16Commission errors (X) 7.35 13.48 7.38 19.49 7.38 21.96 3.11 3.33RT correct answers (X) 983.69 139.58 1,003.72 128.81 961.47 128.95 953.44 144.48RT commission errors (X) 752.29 501.26 876.04 540.71 787.38 470.58 749.27 554.25Motor activity (X) 1.03 1.06 0.61 0.48 0.69 0.46 0.59 0.46Deviation from the focus (X) 14,448.29 26,590.56 6,149.19 19,722.61 6,601.72 20,631.72 4,218.14 12,451.04Blackboard errors (X) 6.78 7.85 7.22 12.03 6.65 12.46 4.24 3.85



M SD M SD M SD M SD

Omission errors (X) 3.16 2.92 2.34 3.44 3.68 5.44 1.96 2.29Commission errors (X) 3.30 3.26 1.97 2.29 10.33 29.09 1.49 1.40RT correct answers (X) 917.28 102.86 897.81 92.10 859.22 112.50 873.91 98.83RT commission errors (X) 710.15 519.64 674.17 621.12 757.90 493.75 577.11 551.19Motor activity (X) 0.61 0.33 0.47 0.41 0.63 0.51 0.41 0.26Deviation from the focus (X) 2,718.27 5,152.46 2,288.93 9,833.99 4,242.39 11,408.49 1,786.10 4,541.52Blackboard errors (X) 3.84 3.28 2.28 2.55 7.52 18.20 2.08 2.12

Table 13. X-Task-Specific Performance (Inattention, 12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

Omission errors (X) 2.38 3.59 2.09 3.70Commission errors (X) 3.68 16.13 4.47 19.88RT correct answers (X) 832.38 112.68 818.23 117.36RT commission

errors (X)621.90 599.36 531.76 587.42

Motor activity (X) 0.51 0.41 0.37 0.23Deviation from the

focus (X)3,606.97 18,716.86 1,082.36 4,781.92

Blackboard errors (X) 3.17 9.89 3.41 11.16




In terms of auditory attention, as represented in Table 18, from 6 to 7 years old, the main difference is the decrease of auditory omission errors (m six = 163.89, m seven = 126.66; U = 7,673.5, p < .001) and an improvement of reaction time when providing correct auditory answers (m six = 155.74, m seven = 134.16; U = 8,799, p < .05). This improvement takes place again from 10 (m = 135.75) to 11 years old (m = 111.91; U = 6,190, p < .01). Finally, latest changes in audi-tory attention show with a significant decrease of auditory commission errors from 9 (m = 152.51) to 10 years old (m = 119.26; U = 6,977.50, p < .001).

With regard to performance under the influence of dis-tractors, omission errors decrease very significantly from 6 to 7 years old (m six = 163.72, m seven = 126.81; U = 7,697, p < .001) and from 7 to 8 years old (m seven = 151.24, m eight = 115.82; U = 6,638.5, p < .001); it is close

Table 14. Total Scores (6-11-Year-Old Groups)



M SD M SD M SD M SD

RT general correct answers 1,018.46 177.95 1,085.68 144.61 964.93 178.39 987.94 112.94Total commission errors 22.88 21.57 16.13 20.50 16.24 10.57 16.18 11.48RT total commission errors 977.33 273.45 1,036.87 333.06 905.22 275.82 965.04 264.94Total omission errors 58.56 39.42 56.77 37.59 42.87 31.55 36.28 23.41Total motor activity 1.23 0.80 0.80 0.55 0.91 0.60 0.76 0.57Total deviation from the

focus49,514.54 62,551.91 56,054.97 144,202.48 29,687.98 54,887.61 23,507.98 39,100.24



M SD M SD M SD M SD

RT general correct answers 899.21 119.34 949.46 123.79 876.34 115.83 912.11 128.06Total commission errors 19.88 16.36 18.25 21.74 19.52 23.00 13.17 7.46RT total commission errors 810.89 226.54 913.33 266.80 796.56 170.33 833.27 235.22Total omission errors 29.94 26.80 27.48 23.91 25.33 24.28 22.96 24.52Total motor activity 0.92 0.87 0.55 0.41 0.66 0.40 0.56 0.40Total deviation from the

focus23,641.39 47,193.54 8,464.55 24,506.44 11,885.20 28,024.27 8,562.11 24,200.00



M SD M SD M SD M SD

RT general correct answers 857.48 139.66 873.65 101.16 826.80 101.95 834.65 106.50Total commission errors 15.30 7.82 9.49 5.35 20.82 30.07 9.59 5.69RT total commission errors 757.77 190.37 816.12 261.06 798.62 223.00 725.53 240.25Total omission errors 18.89 18.89 21.99 32.56 19.55 20.86 15.92 21.57Total motor activity 0.57 0.28 0.45 0.40 0.57 0.38 0.39 0.26Total deviation from the

focus6,295.02 13,531.47 4,454.52 22,366.670 7,113.58 17,346.15 4,839.33 17,312.37

Table 15. Total Scores (12-16-Year-Old Groups)

12-16 years old

Boys (n = 241) Girls (n = 234)

M SD M SD

RT general correct answers

795.93 112.30 789.45 108.91

Total commission errors

12.17 17.34 11.79 21.19

RT total commission errors

696.94 221.85 696.72 245.19

Total omission errors 13.08 19.46 10.20 14.93Total motor activity 0.48 0.36 0.35 0.20Total deviation from

the focus5,963.61 28,867.38 1,862.44 8,686.08



Iriarte et al. 13

to statistical significance from 8 to 9 years old (p = .076) and shows again a decrease from 9 to 10 years old (m nine = 145.94, m ten = 126.34; U = 7,904.5, p < .05), not

showing statistically significant decreases in subsequent age groups. Reaction time needed to provide correct answers decreases (i.e., improves) from 6 to 7 years old (m

Table 16. Overall Gender Differences in the Normative Group (N = 1,272)

Significant differences by gender

Category/cluster m boys (n = 659) m girls (n = 613)Mann–Whitney

U test p

Visual attention Visual omission errors 657.21 614.23 188,333.5 .037 Visual commission errors 694.85 573.77 163,528 .000 RT visual correct answers n.s. RT visual commission errors n.s.Auditory attention Auditory omission errors 659.06 612.25 187,115.5 .022 Auditory commission errors 685.26 584.08 169,850 .000 RT auditory correct answers n.s. RT auditory commission errors n.s.Performance with distractors Omission errors with distractors 659.02 612.29 187,145 .023 Commission errors with distractors 686.03 583.25 169,343 .000 RT correct answers with distractors n.s. RT Commission errors with distractors n.s. Motor activity with distractors 721.36 545.28 146,063 .000 Deviation from the focus with distractors 679.36 590.42 173,738.5 .000Performance without distractors Omission errors without distractors 663.87 607.08 183,947.5 .006 Commission errors without distractors 697.29 571.15 161,926 .000 RT correct answers without distractors n.s. RT commission errors without distractors n.s. Motor activity without distractors 718.74 548.08 147,785 .000 Deviation from the focus without distractors 682.66 586.87 171,562 .000No-X task performance Omission errors (No-X) 658.46 612.89 187,509.5 .027 Commission errors (No-X) 692.26 576.56 165,239.5 .000 RT correct answers (No-X) 615.37 659.22 177,503.5 .033 RT commission errors (No-X) n.s. Motor activity (No-X) 717.27 549.67 148,757.5 .000 Deviation from the focus (No-X) 678.75 591.08 174,144 .000 Blackboard errors (No-X) 673.65 596.57 177,503 .000X task performance Omission errors (X) 667.58 603.08 181,499 .002 Commission errors (X) 687.53 581.64 168,357 .000 RT correct answers (X) n.s. RT commission errors (X) n.s. Motor activity (X) 718.82 548.00 147,735 .000 Deviation from the focus (X) 682.35 587.21 171,767 .000 Blackboard errors (X) 676.04 593.99 175,923 .000Total scores RT general correct answers n.s. Total commission errors 699.54 568.73 160,439.5 .000 RT total commission errors n.s. Total omission errors 662.21 608.86 185,041.5 .01 Total motor activity 721.21 545.43 146,157.5 .000 Total deviation from the focus 686.76 582.47 168,860.5 .000

Note: n.s. = nonsignificant (p > .05); m = mean rank.




six = 158.92, m seven = 131.24; U = 8,360.5, p < .01), from 7 to 8 years old (m seven = 146.53, m eight = 121.72; U = 7,346, p < .01), and finally from 8 to 9 years old (m eight = 142.01, m nine = 121.63; U = 7,138.5, p < .05). Commission errors in the presence of distractors only show significant changes with an increase occurring from 7 to 8 years old (m seven = 127.01, m eight = 146.11; U = 7,726.5, p < .05) and a decrease from 9 (m = 145.98) to 10 years old (m = 126.30; U = 7,899, p < .05); changes in reaction time for correct answers only show from 7 to 8 years old (m seven = 144.20, m eight = 124.62; U = 7,694.5, p < .05), whereas changes in reaction time for commission errors appear only from 11 to 12 years old (m eleven = 142.15, m twelve = 121.94; U = 7,329.5, p < .05). Distractors also show influence on motor activity with a significant

decrease (i.e., improvement) from 6 to 7 years old (m six = 156.21, m seven = 133.73; U = 8,734.5, p < .05), 7 to 8 years old (m seven = 149.22, m eight = 118.35; U = 6,942, p < .01), and 9 to 10 years old (m nine = 146.87, m ten = 125.34; U = 7,773, p < .05). Finally, deviation from the focus shows a significant improvement from 7 (m = 148.39) to 8 years old (m = 119.39; U = 7,067, p < .01) and from 11 to 12 years old (m eleven = 140.35, m twelve = 123.40; U = 7,329.5, p < .05). Table 19 represents a fast overview of the changes stated above.

Regarding performance in absence of distractors, sum-marized in Table 20, omission errors’ incidence decreases significantly with age from 6 (m = 156.21) to 7 years old (m = 133.73; U = 7,697, p < .001), from 7 (m = 150.87) to 8 years old (m = 116.28; U = 6,694, p < .01), and from 9

Table 17. Changes in Visual Attention According to Age

Category/cluster Significant differences by age

Visual attention 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Visual omission errors > > n.s. > n.s. >n.s. n.s. n.s. n.s. n.s.Visual commission errors n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.RT visual correct answers > > n.s. > n.s. >n.s. n.s. n.s. n.s. n.s.RT visual commission errors > n.s. n.s. > > n.s. n.s. n.s. n.s. n.s.

Note: > = the value decreases as age increases; < = the value increases as age increases; n.s = the change is nonsignificant.

Table 18. Changes in Auditory Attention According to Age


Auditory attention 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Auditory omission errors > n.s. n.s. n.s. n.s n.s n.s. n.s. n.s. n.s.Auditory commission errors n.s. n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT auditory correct answers > n.s. n.s. n.s. > n.s n.s. n.s. n.s. n.s.RT auditory commission errors n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.

Note: > = the value decreases as age increases; < = the value increases as age increases; n.s. = the change is nonsignificant.

Table 19. Changes in Performance With Distractors Present According to Age


Performance with distractors 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Omission errors with distractors > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Commission errors with distractors < n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT correct answers with distractors n.s. > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.RT commission errors with distractors n.s. n.s. n.s. n.s. n.s. > n.s. n.s. n.s. n.s.Motor activity with distractors > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Deviation from the focus with distractors n.s. > n.s. n.s. n.s. > n.s. n.s. n.s. n.s.




Iriarte et al. 15

(m = 148.03) to 10 years old (m = 124.09; U = 7,609.5, p < .05). Commission errors only show a significant decrease from 9 (m = 147.30) to 10 years old (m = 124.87; U = 7,712, p < .05). One of the most visible changes associated with age in absence of distractors is the reaction time when providing correct answers. It decreases significantly from 6 to 7 years old (m six = 165.23, m seven = 125.43; U = 7,489, p < .001), 7 to 8 years old (m seven = 151.33, m eight = 115.72; U = 6,626, p < .001), 8 to 9 years old (m eight = 144.29, m nine = 119.69; U = 6,865, p < .01), 9 to 10 years old (m nine = 148.23, m ten = 123.88; U = 7,582, p < .05), and 10 to 11 years old (m ten = 135.86, m eleven = 111.78; U = 6,175.5, p < .01). Motor activity in absence of distractors decreases (i.e., improves) from 6 (m = 157.71) to 7 years old (m = 132.34; U = 8,526.5, p < .05) and 9 (m = 148.70) to 10 years old (m = 123.37; U = 7,515, p < .01). Finally, deviation from the focus gets significantly reduced (i.e., improved) from 6 (m = 159.21) to 7 years old (m = 130.96; U = 8,319, p < .01) and from 7 (m = 152.34) to 8 years old (m = 114.45; U = 6,474.5, p < .01).

At No-X-task-specific performance (summarized in Table 21), related to impulsivity, significant changes occur from 6 to 7 years old for most of the variables. More spe-cifically, there is a decrease of omission errors (m six = 162.63, m seven = 127.82; U = 7,848.5, p < .001); the reaction time required to provide correct answers also

improves (m six = 160.03, m seven = 130.22; U = 8,207.5, p < .01), and both motor activity (m six = 156.99, m seven = 133.01; U = 8,626, p < .05) and deviation from the focus improve with age at this point (m six = 158.11, m seven = 131.98; U = 8,472.5, p < .01); blackboard errors also reduce (m six = 158.48, m seven = 131.64; U = 8,421, p < .001). The same improvements occur with age from 7 to 8 years old (omissions, p < .001; reaction time for correct answers, p < .01; reaction time for commission errors, p < .05; motor activity, p < .01; deviation from the focus, p < .01; blackboard errors, p < .001). From 8 to 9 years old, the only significant change is an improvement of reaction time needed to provide correct answers (m eight = 141.98, m nine = 121.65; U = 7,138.5, p < .05). Further changes take place from 9 to 10 years old, where omission errors, reaction time for correct answers, and deviation from the focus improve but do not reach statistical significance. What appears to be significant is the reduction of No-X commission errors (m nine = 147.05, m ten = 125.15; U = 7,748, p < .05), improvement of motor activity (m nine = 149.13, m ten = 122.91; U = 7,455, p < .01), and decrease of blackboard errors (m nine = 147.84, m ten = 124.29; U = 7,636.5, p < .05). No further age-associated signifi-cant changes appear for No-X task, except for a decrease in blackboard errors from 11 (m = 142.09) to 12 years old (m = 121.99; U = 7,126.5, p < .05).

Table 20. Changes in Performance Without Distractors According to Age


Performance without distractors 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Omission errors without distractors > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Commission errors without distractors n.s. n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT correct answers without distractors > > > > > n.s. n.s. n.s. n.s. n.s.RT commission errors without distractors n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Motor activity without distractors > n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Deviation from the focus without distractors > > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.


Table 21. No-X-Task-Specific Changes in Performance According to Age


No-X task performance 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Omission errors (No-X) > > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Commission errors (No-X) n.s. n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT correct answers (No-X) > > > n.s. n.s. n.s. n.s. n.s. n.s. n.s.RT commission errors (No-X) n.s. > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Motor activity (No-X) > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Deviation from the focus (No-X) > > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Blackboard errors (No-X) > > n.s. > n.s. > n.s. n.s. n.s. n.s.





Regarding X-task-specific performance (represented in Table 22), related to inattention, many changes occur from 6 to 7 years old. Omission errors (m six = 168.69, m seven = 122.24; U = 7,011.5, p < .001) as well as commission errors (m six = 159.25, m seven = 130.93; U = 8,314, p < .01), reac-tion time needed to provide correct answers (m six = 166.11, m seven = 124.62; U = 7,368, p < .001), motor activity (m six = 157.50, m seven = 132.54; U = 8,556.50, p < .05), deviation from the focus (m six = 160.58, m seven = 129.71; U = 8,131.5, p < .01), and blackboard errors (m six = 167.89, m seven = 122.98; U = 7,122, p < .001) significantly decrease. From 7 to 8 years old, this trend only applies to improvements in reaction time for correct answers (m seven = 152.93, m eight = 113.71; U = 6,385, p < .001), motor activity (m seven = 148.43, m eight = 119.34; U = 7,061, p < .01), and deviation from the focus (m seven = 147.87, m eight = 120.04; U = 6,934.50, p < .01). From 8 to 9 years old, main changes occur in rate improvements for omission errors (m eight = 141.88, m nine = 121.74; U = 7,154.5, p < .05) and reaction time for correct answers (m eight = 145.79, m nine = 118.41; U = 6,685, p < .01). From 9 to 10 years old, there are less omission errors (m nine = 152.27, m ten = 119.53; U = 7,012.50, p < .01), less commis-sion errors (m nine = 145.61, m ten = 126.70; U = 7,951.5, p < .05), shorter reaction time for correct answers (m nine = 149.43, m ten = 122.58; U = 7,412, p < .01), a better motor activity (m nine = 147.40, m ten = 124.77; U = 7,698.5, p < .05), and less blackboard errors (m nine = 151.94, m ten = 119.88; U = 7,058, p < .01). From 10 to 11 years old, only reaction time to correct answers appears to be significant (m ten = 139.11, m eleven = 108.15; U = 5,750, p < .01), and from 11 to 12 years old, a significant improvement appears for deviation of the focus (m eleven = 140.43, m twelve = 123.34; U = 7,320.5, p < .023).

Finally, in terms of total scores, significant differences from 6 to 7 years old include reduction of total omission errors (m six = 164.82; m seven = 125.80; U = 7,545.50, p < .001), shorter reaction time to total correct answers (m six = 164.81, m seven = 125.81; U = 7,547, p < .001),

shorter reaction time when performing commission errors (m six = 150.89, m seven = 138.62; U = 8,641.5, p < .05), less total motor activity (m six = 157.33, m seven = 132.69; U = 8,579, p < .05), and less total deviation from the focus (m six = 159.08, m seven = 131.08; U = 8,337.5, p < .01). Similar changes occur from 7 to 8 years old as follows: less omission errors (m seven = 151.53, m eight = 115.46; U = 6,595, p < .001), shorter reaction time to total correct answers (m seven = 149.42, m eight = 118.10; U = 6,912, p < .01), shorter reaction time when performing commis-sion errors (m seven = 144.63, m eight = 124.09; U = 7,631, p < .05), lower total motor activity (m seven = 149.14, m eight = 118.45; U = 6,954, p < .01), and less total deviation from the focus (m seven = 152.67, m eight = 114.03; U = 6,424, p < .001). From 8 to 9 years old, the only significant change takes place in a shorter reaction time to correct answers (m eight = 143.58, m nine = 120.29; U = 6,950.5, p < .05). From 9 to 10 years old, changes occur again for most of the measures: less total omission errors (m nine = 147.74, m eleven = 124.40; U = 7,650.5, p < .05), less total commission errors (m nine = 147.91, m ten = 124.21; U = 7,626, p < .05), shorter reaction time to total correct answers (m nine = 146.48, m ten = 125.76; U = 7,829, p < .05), and less total motor activity (m nine = 147.87, m ten = 124.26; U = 7,632, p < .05). From 10 to 11 years old, the only sig-nificant change takes place in reaction time to correct answers (m ten = 135.13, m eleven = 112.60; U = 6,271, p < .05), and from 11 to 12 years old, a significant change occurs in total deviation from the focus (m eleven = 141.40, m twelve = 122.55; U = 7,207, p < .05). An overview of changes in total scores can be seen in Table 23.

Overall, as it has been shown in Tables 17 to 23, there were no statistically significant differences between chil-dren of the group ranging from 12 to 16. Subsequently, this led to the elaboration of 14 normative groups, 7 for each gender. The first 6 belonged to individual age groups (6, 7, 8, 9, 10, and 11 years old), and the last one grouped all the children assessed whose age was between 12 and 16 years.

Table 22. X-Task-Specific Changes in Performance According to Age


X task performance 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

Omission errors (X) > n.s. > > n.s. n.s. n.s. n.s. n.s. n.s.Commission errors (X) > n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT correct answers (X) > > > > > n.s. n.s. n.s. n.s. n.s.RT commission errors (X) n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Motor activity (No-X) > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Deviation from the focus (X) > > n.s. n.s. n.s. > n.s. n.s. n.s. n.s.Blackboard errors (X) > n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.




Iriarte et al. 17

Below, we present gender differences within each age group, and finally, an overview of differences between visual and auditory attention is presented.

Gender Differences in Interaction With AgeWithin each age group, Mann–Whitney U tests were per-formed to determine the existence of differences between boys and girls of the same age among the main variables described.

Six years old: gender differences. For visual attention, sig-nificant differences appeared for commission errors, which were higher for boys than for girls, while boys seemed to be faster when reacting and providing correct answers. For auditory attention, the pattern was identical. Performance under the influence of distractors was similar but showed additionally that boys were more influenced by distractors and performed worse than girls as they increased their motor activity under the influence of distractors. However, this performance was similar, and boys were worse in the same type of measures when distractors were absent. With regard to performance in No-X task, more related to impul-sivity, the trend maintained in the same way: more commis-sion errors in boys than in girls, faster answers for boys when reacting and providing correct answers, and worse motor activity performance for boys. Regarding perfor-mance in X task, more related to inattention, differences maintain in commission errors and motor activity. In addi-tion, a higher deviation from the focus appeared for boys than for girls. The general pattern described is also trans-ferred to total scores. Table 24 shows these results in detail.

Seven years old: gender differences. For this age group, there were no statistically significant differences based on gender for either visual attention or auditory attention. When distractors were introduced, motor activity was worse in boys, as it was when distractors were absent. Motor activity was also worse in boys when related to X task per-formance and as its total measure, as is seen in Table 25.

Eight years old: gender differences. For visual attention, there were no statistically significant differences based on

gender for this age group. For auditory attention, boys pro-vided faster auditory correct answers than girls.

For performance under the influence of distractors, reac-tion time was significantly faster when providing correct answers in boys than in girls. However, the performance with regard to motor activity and deviation from the focus was worse in boys when distractors were present. In the absence of distractors, boys were faster providing correct answers and, once again, performed worse for motor activ-ity and deviation from the focus.

With regard to performance in No-X task, related to impulsivity, boys provided not only faster correct answers but also faster commission errors; and their motor activity and deviation from the focus were higher (i.e., worse) than for girls in No-X task.

Regarding performance in X task, boys were still worse performers in relation to motor activity and deviation from the focus.

For total scores, the same pattern appeared related to shorter reaction time in boys for both correct answers and commission errors, together with worse motor activity and deviation from the focus. Table 26 shows all these differ-ences in a clear overview.

Nine years old: gender differences. For visual attention, boys showed a significantly higher rate of visual commis-sion errors than girls. For auditory attention, boys provided faster auditory correct answers. In addition, for performance under the influence of distractors, boys performed a higher rate of commission errors and a higher (i.e., worse) motor activity. On the contrary, in absence of distractors, increased motor activity in boys was the only significant difference. The same unique differences on motor activity took place in No-X task and X task. For total scores, main significant dif-ferences indicated a worse performance of boys on the higher rate of total commission errors and higher total motor activity. Table 27 shows a summary of the obtained differences.

Ten years old: gender differences. For both visual and audi-tory attention, boys showed a higher rate of commission

Table 23. Total Scores’ Changes According to Age


Total scores 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16

RT general correct answers n.s. > > > > n.s. n.s. n.s. n.s. n.s.Total commission errors n.s. n.s. n.s. > n.s. n.s. n.s. n.s. n.s. n.s.RT total commission errors > > n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.Total omission errors > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Total motor activity > > n.s. > n.s. n.s. n.s. n.s. n.s. n.s.Total deviation from the focus > > n.s. n.s. n.s. > n.s. n.s. n.s. n.s.





Table 24. Gender Differences in Interaction With Age (6-Year-Old Group, n = 138)



U test p

Visual attention Visual commission errors 77.17 59.53 1,742 .01 RT Visual correct answers 60.98 80.58 1,675.5 .004Auditory attention Auditory commission errors 76.87 59.92 1,765 .013 RT auditory correct answers 62.71 78.33 1,810 .023Performance with distractors Commission errors with distractors 77.31 59.34 1,730.5 .009 RT correct answers with distractors 59.53 82.47 1,562 .001 Motor activity with distractors 79.21 56.88 1,582.5 .001Performance without distractors Commission errors without distractors 77.96 58.50 1,680 .005 RT correct answers without distractors 63.05 77.88 1,837 .031 Motor activity without distractors 79.21 56.88 1,462.5 .000No-X task performance Commission errors (No-X) 76.81 60.00 1,770 .014 RT correct answers (No-X) 60.13 81.68 1,609 .002 Motor activity (No-X) 78.08 58.34 1,670.5 .004X task performance Commission errors (X) 78.45 57.87 1,642 .003 Motor activity (X) 81.01 54.53 1,442 .000 Deviation from the focus (X) 76.65 60.20 1,782 .016Total scores RT general correct answers 61.65 79.70 1,728 .009 Total commission errors 78.30 58.06 1,653.5 .003 Total motor activity 80.10 55.72 1,513 .000

Note: m = mean rank.




U test p

Motor activity with distractors 82.01 65.73 2,114 .025Motor activity without distractors 81.17 67.00 2,190 .050Motor activity (X) 82.01 65.73 2,114 .025Total motor activity 81.49 66.51 2,160.5 .038


errors. Under the influence of distractors, commission errors appeared again as representative of boys’ poorer per-formance, together with a higher motor activity and a greater deviation from the focus. Interestingly, absence of distractors did not change the picture at all, and the same pattern applied to performance in No-X task (commission errors were again higher in boys, as higher were the motor activity and deviation from the focus).

Regarding performance in X task, all types of error rates as well as motor activity and deviation from the focus were higher in boys (i.e., omission errors, commission errors, and

blackboard errors). Total scores were a partial reflection of the pattern seen above: statistically significant differences show a worse performance of 10-year-old boys versus girls in total commission errors, total motor activity, and total deviation from the focus. These differences can be rapidly confirmed in Table 28.

Eleven years old: gender differences. For visual attention, statistically significant differences showed a higher rate of commission errors in boys, similarly as in previous age groups, but a higher reaction time when performing com-mission errors in boys, which was not seen before. For



Iriarte et al. 19




U test p

Auditory attention RT auditory correct answers 51.65 67.04 1,308 .017Performance with distractors RT correct answers with distractors 52.53 66.39 1,353 .031 Motor activity with distractors 72.30 51.78 1,157.5 .001 Deviation from the focus with distractors 68.39 54.67 1,357 .016Performance without distractors RT correct answers without distractors 52.84 66.16 1,369 .038 Motor activity without distractors 70.98 52.75 1,225 .005 Deviation from the focus without distractors 68.71 54.43 1,341 .016No-X task performance RT correct answers (No-X) 52.42 66.47 1,347.5 .029 RT commission errors (No-X) 53.25 65.86 1,390 .050 Motor activity (No-X) 73.06 51.22 1,119 .001 Deviation from the focus (No-X) 66.95 55.73 1,430.5 .049X task performance Motor activity (X) 70.47 53.13 1,251 .007 Deviation from the focus (X) 68.16 54.84 1,369 .025Total scores RT general correct answers 71.67 52.25 1,348 .029 RT total commission errors 68.76 54.39 1,360 .034 Total motor activity 71.67 52.25 1,190 .002 Total deviation from the focus 68.76 54.39 1,338 .019





U test p

Visual attention Visual commission errors 80.18 62.20 1,850.5 .009Auditory attention RT auditory correct answers 63.83 77.88 1,989 .041Performance with distractors Commission errors with distractors 80.78 61.63 1,809 .005 Motor activity with distractors 79.92 62.45 1,868.5 .011Performance without distractors Motor activity without distractors 78.70 63.62 1,989.5 .028No-X task performance Motor activity (No-X) 79.64 62.72 1,887.5 .014X task performance Motor activity (X) 78.17 64.13 1,989.5 .041Total scores Total commission errors 79.13 63.21 1,923 0.21 Total motor activity 79.26 63.08 1,914 .019





auditory attention, the rates of both auditory omissions and commission errors were higher for boys than for girls, and reaction time for commission errors were again higher in boys than in girls at this age.

For performance under the influence of distractors, boys showed, as in previous age groups, a higher motor activity as well as a larger deviation from the focus than girls. When distractors were absent, apart from these same significant differences in motor activity and deviation from the focus, commission errors and time taken to perform them were significantly higher in boys than in girls at this age.

With regard to performance in No-X task, commission errors’ rate, and motor activity and deviation from the focus were higher in boys than in girls.

Regarding performance in X task, again, commission errors, motor activity, and deviation from the focus showed worse scores for boys; moreover, blackboard errors in X task were significantly higher for boys at this age.

Finally, total scores were a partial reflection of what appeared separately in each scoring cluster separately. Thus, for total scores, statistically significant differences showed

a worse performance of 11-year-old boys versus girls in total commission errors, total motor activity, and total devi-ation from the focus. Differences for this age group are summarized in Table 29.

Twelve to sixteen years old: gender differences. For visual attention, this composite age group showed statistically sig-nificant differences in favor of girls in visual commission errors, where boys show a worse performance. For auditory attention, there were no statistically significant differences among gender groups at these ages.

For performance under the influence of distractors, boys showed a worse performance in motor activity and in devia-tion from the focus. For performance in absence of distrac-tors, boys showed a higher rate of commission errors and higher motor activity.

With regard to performance in No-X task, commission errors’ rate was higher in boys than in girls, and the same pattern occurred for motor activity, deviation from the focus, and No-X blackboard errors. Regarding perfor-mance in X task, differences also appeared in commission errors’ rate, which was higher in boys, and the same



Category/cluster m boys (n = 64) m girls (n = 67) Mann–Whitney U test p

Visual attention Visual commission errors 79.73 52.89 1,265.5 .000Auditory attention Auditory commission errors 78.28 54.27 1,358 .000Performance with distractors Commission errors with distractors 77.98 54.56 1,377.5 .000 Motor activity with distractors 78.62 53.95 1,336.5 .000 Deviation from the focus with distractors 73.82 58.53 1,643.5 .003Performance without distractors Commission errors without distractors 81.45 51.25 1,155.5 .000 Motor activity without distractors 79.73 52.89 1,265.5 .000 Deviation from the focus without distractors 76.83 55.66 1,451 .000No-X task performance Commission errors (No-X) 81.62 51.08 1,144.5 .000 Motor activity (No-X) 77.59 54.93 1,402 .001 Deviation from the focus (No-X) 75.66 56.78 1,526 .000X task performance Omission errors (X) 75.26 57.16 1,551.5 .005 Commission errors (X) 76.06 56.39 1,500 .003 Motor activity (X) 79.40 53.20 1,286.5 .000 Deviation from the focus (X) 73.33 59.00 1,675 .012 Blackboard errors (X) 76.15 56.31 1,494.5 .002Total scores Total commission errors 81.47 51.22 1,154 .000 Total motor activity 79.74 52.87 1,264.5 .000 Total deviation from the focus 78.41 54.15 1,350 .000




Iriarte et al. 21

happened with motor activity. Finally, for total scores, the same scores were affected and in the same direction of showing a worse performance in boys for commission errors and motor activity. Table 30 summarizes the results explained above.

Comparison Between Visual and Auditory Attention in Interaction With Age and Gender

Finally, Wilcoxon’s test analyses were performed to ana-lyze existing differences between the two sensory modali-ties that can be evaluated in AULA in relation to attention processes, that is, visual attention versus auditory attention. A general comparison between visual variables and their analogous auditory ones showed statistically significant differences for all the variables, showing a significantly higher occurrence of visual omissions and commissions

(vs. their auditory analogous) as well as a shorter reaction time to provide visual answers, both when they are correct and when they mean errors of commissions (i.e., pressing the button when the child should have not pressed it), as can be seen in Table 31.

Table 32 shows the differences between visual and audi-tory attention for the 6-year-old group. As can be seen in Table 32, visual omissions are more frequent than auditory omissions, and time required to provide visual answers is shorter for correct and for commission errors than the time required for auditory responses.

For 7-year-old children, results show a similar trend with an added difference, as it appears to be a higher rate for visual versus auditory commissions, which in the case of girls reaches statistical significance (see Table 33).

For those who are 8 years old, either boys or girls, per-formance shows a significantly higher rate of visual errors (both omission and commissions) and a shorter time to provide visual answers when compared with time required




Visual attention Visual omission errors 67.55 47.93 1,118.5 .002 RT visual commission errors 65.86 50.12 1,230 .013Auditory attention Auditory omission errors 65.31 50.83 1,266.5 .020 Auditory commission errors 66.80 48.91 1,168.5 .004 RT auditory commission errors 65.39 50.73 1,261 .020Performance with distractors Motor activity with distractors 68.61 46.57 1,049 .000 Deviation from the focus with distractors 65.68 50.35 1,242 .003Performance without distractors Commission errors without distractors 70.05 44.71 954 .000 RT commission errors without distractors 65.79 50.22 1,235 .014 Motor activity without distractors 67.74 47.69 1,106 .002 Deviation from the focus without distractors 65.14 51.06 1,278 .008No-X task performance Commission errors (No-X) 65.21 50.96 1,273 .024 Motor activity (No-X) 68.77 46.35 1,038 .000 Deviation from the focus (No-X) 63.69 52.93 1,373.5 .021X task performance Commission errors X 67.67 47.78 1,111 .001 Motor activity X 67.16 48.44 1,144.5 .003 Deviation from the focus X 65.35 50.78 1,264 .007 Blackboard errors X 65.23 50.94 1,272 .022Total scores Total commission errors 68.11 47.21 1,081.5 .001 Total motor activity 68.30 46.97 1,069.5 .001 Total deviation from the focus 66.12 49.78 1,213 .003





to provide auditory answers, despite that they are correct or commission errors. These tendencies repeat in all the subsequent age groups, as can be seen summarized in Table 34.

ConclusionThe present study has presented the first data that were obtained from the normative study of AULA as a new eco-logical attention test. As it has been seen in preceding pages, there was a general pattern of gender differences showing a trend to faster answers (both correct and incorrect—commission errors) for boys in most of the age

groups, greater motor activity (more head movement that prevents a better performance in the test), and greater deviation from the focus (which means that the child is not looking permanently where he or she is supposed to look at—that is, the virtual blackboard). Seen from the other perspective, girls may appear slower in providing answers, but they show a better performance in all types of tasks (X, No-X) and conditions (with and without distractors). Regarding age differences, they seem to be more clear in the initial age groups (from 6 to 7 years old and 7 to 8 years old), whereas they are not so obvious in subsequent age groups, especially after 10 years old, leading to nonsignifi-cance from the age of 12. In this sense, all participants between 12 and 16 years showed stable attentional param-eters despite the age differences, so it is possible that this stability may be suggestive of the normal evolutive devel-opment of cognitive processes measured with this test in these age ranges. However, further studies are required to confirm this latest assumption.

The current normative study comprises evident limita-tions. The AULA test was developed based on two atten-tion models derived from the study of ADHD (Sergeant et al.’s state regulation model and Barkley’s unique deficit model) but without further studies and use of the test, and only based on this population study, it is difficult to ensure the sensitivity and specificity of the test to differentiate ADHD from normally evolving children. In addition, inclusion of other ethnical and cultural groups has never

Table 30. Gender Differences in Interaction With Age (12-16-Year-Old Groups, n = 475)



Visual attention Visual commission errors 256.41 219.03 23,759 .003Performance with distractors Motor activity with distractors 267.45 207.67 21,100.5 .000 Deviation from the focus with distractors 246.88 228.85 26,056.5 .026Performance without distractors Commission errors without distractors 255.34 220.14 24,018 .005 Motor activity without distractors 267.97 207.13 20,974.5 .000No-X task performance Commission errors (No-X) 256.68 218.76 23,694.5 .003 Motor activity (No-X) 267.82 207.29 21,011 .000 Deviation from the focus (No-X) 247.82 227.89 25,831 .012 Blackboard errors (No-X) 253.04 222.51 24,573 .015X task performance Commission errors (X) 252.32 223.26 24,747 .016 Motor activity (X) 266.66 208.49 21,291 .000Total scores Total commission errors 256.71 218.73 23,688.5 .003 Total motor activity 268.19 206.91 20,921 .000


Table 31. Differences Between Visual and Auditory Attention for the Total Sample

N = 1,272 M SD z p

Visual omissions 17.56 20.92 −22.557 0.000Auditory omissions 6.94 12.15 Visual commissions 8.83 9.78 −19.290 0.000Auditory commissions 6.04 9.27 RT visual correct 701.25 165.92 −30.731 0.000RT auditory correct 1,042.96 160.40 RT visual commissions 701.24 165.92 −25.206 0.000RT auditory commissions 1,057.96 438.02



Iriarte et al. 23

Table 32. Differences Between Visual and Auditory Attention for the 6-Year-Old Group

Boys (n = 78) Girls (n = 60)

6 years old (n = 138) M SD z p M SD z p

Visual omissions 40.92 25.91 −6.232 .000 41.70 24.99 −6,214 .000Auditory omissions 17.64 22.32 15.07 19.15 Visual commissions 11.22 10.23 −0.178 .859 8.08 10.52 −0.426 .670Auditory commissions 11.67 12.38 8.05 10.49 RT visual correct 875.01 246.25 −7.150 .000 943.17 201.45 −6.567 .000RT auditory correct 1,118.61 171.73 1,187.89 156.74 RT visual commissions 776.68 345.94 −5.918 .000 845.05 394.22 −4.982 .000RT auditory commissions 1,143.40 407.85 1,170.32 400.76

Table 33. Differences Between Visual and Auditory Attention for the 7-Year-Old Group

Boys (n = 90) Girls (n = 60)


Visual omissions 33.93 24.38 −7.575 .000 28.55 20.09 −6.519 .000Auditory omissions 8.93 13.54 7.73 8.32 Visual commissions 8.82 6.57 −1.931 .053 8.88 5.81 −2.496 .013Auditory commissions 7.42 5.37 7.30 6.67 RT visual correct 810.69 246.25 −8.046 .000 828.69 132.04 −6.662 .000RT auditory correct 1,084.98 200.56 1,119.84 127.76 RT visual commissions 670.06 260.41 −7.481 .000 746.39 250.76 −5.587 .000RT auditory commissions 1,126.26 352.34 1,172.54 449.06

Table 34. Differences Between Visual and Auditory Attention for Groups Aged 8 to 12 to 16 Years

Boys (n = 51) Girls (n = 69)



Boys (n = 69) Girls (n = 72)



(continued)




been an issue in Spain, as the percentage of immigrants was generally low and never had the attention and interest shown in other countries like the United States. In other words, the sampling was incidental, and the representation of ethnicity was minimal as it is minimal in the schools where the test was administered. No child was excluded because of cultural or ethnic reasons, but no particular effort was made to include different ethnic groups. Hence, for international cross-cultural validation of AULA, this remains an open issue. In addition, there is a need to evalu-ate the efficacy of the test in clinical populations with dif-ferent profiles of neurodevelopmental disorders. As a test for measuring attention, it may be useful for the evaluation of traumatic brain injury in children, but it is a field that has not been studied yet.

In this sense, based on this normative study on general population, future studies of AULA should focus on broad-ening the inclusion of different clinical populations of chil-dren and adolescents who may show attentional problems

(ADHD is one of them but not the only) to check AULA’s sensitivity and specificity to differentiate between different pathologies or between pathological conditions and nor-mally evolving children; it could also be used with popula-tions of different cultural and ethnical backgrounds, and at this point, validation in foreign countries different from Spain would add value to the usefulness of the AULA test as an internationally used test for measuring attention.

In general, the advantages provided by VR in terms of immersion in the context of a “real” classroom (with dis-tractors that may appear in daily life situations) facilitate the emulation and transfer of results from the test to real-life contexts, thus increasing the accuracy of the attentional problems that children may face at school in their actual classrooms. It is expected that future work will provide results about the convergent validity of AULA with other tests measuring attention and also about the sensitivity of the AULA test to differentiate between children with differ-ent attentional problems.

Boys (n = 64) Girls (n = 67)



Boys (n = 66) Girls (n = 51)


Visual omissions 12.82 15.90 −4.273 .000 12.75 18.81 −4.903 .000Auditory omissions 6.73 12.20 3.18 5.45 Visual commissions 12.65 17.54 −5.236 .000 6.12 4.35 −3.591 .000Auditory commissions 8.17 13.96 3.47 2.93 RT visual correct 633.49 91.97 −7.062 .000 654.96 103.32 −6.215 .000RT auditory correct 1,020.99 124.97 1,005.10 113.71 RT visual commissions 601.83 247.65 −6.359 .000 532.42 245.34 −5.025 .000RT auditory commissions 1,145.21 385.76 981.60 382.35

Boys (n = 241) Girls (n = 234)

12-16 years old (n = 475) M SD z p M SD z p

Visual omissions 8.70 13.76 −6.402 .000 6.88 10.55 −7.657 .000Auditory omissions 4.39 8.26 3.32 5.78 Visual commissions 7.91 9.22 −11.468 .000 7.22 10.65 −10.317 .000Auditory commissions 4.26 8.49 4.57 10.83 RT visual correct 606.92 103.04 −13.458 .000 614.82 99.18 −13.262 .000RT auditory correct 988.24 142.37 969.11 133.31 RT visual commissions 515.29 187.23 −10.363 .000 506.69 221.36 −10.543 .000RT auditory commissions 969.09 483.04 956.36 459.56

Table 34. (continued)



Iriarte et al. 25

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Yahaira Iriarte, Unai Diaz-Orueta, Gema Climent and Flavio Banterla are employees of the company Nesplora, Technology & Behavior, where the AULA test was developed. Eduardo Cueto from University of Oviedo (Spain) provided expertise and support in the statistical analyses developed for the obtention of normative data.

Funding

The author(s) declared receipt of the following financial support for the research, authorship, and/or publication of this article. The study conducted here was supported by the Centre of Industrial Technological Development of Spain, under the NEOTEC fund-ing program (reference number IDI-20110031).

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Bios

Yahaira Iriarte, MSc degree (graduated in psychology), master’s degree in clinical psychology and neuropsychology at the University of Deusto (Bilbao, Spain), obtained her advanced stud-ies diploma (DEA—Diploma de Estudios Avanzados), with her predoctoral work about “cognitive, behavioural and functional

decline prior to an ictus.” She has worked for more than 3 years with children and adults performing cognitive assessments and rehabilitation. At Nesplora, she works as a researcher at the Research, Development, and Innovation (R+D+I) department. She also works part-time as a teacher at the University of Deusto (Bilbao, Spain), lecturing about “biological basis of behaviour” for undergraduate psychology students, and cooperates in the module of neuropsychological assessment of the mental health master courses of the same university. She has participated in many scientific and dissemination forums, and has performed multiple oral presentations about the scientific characteristics of different tools developed by Nesplora Ltd.

Unai Diaz-Orueta received his PhD in psychology from the University of Deusto (Bilbao, Spain) in 2006, after graduating from the same university in 2000. He has experience as a clinical psychologist from 2000 to 2006 in different settings: Crownsville Hospital Center, Maryland, USA (2000-2001), Bermeo Psychiatric Hospital, Spain (2001-2002), La Loma Geriatric residence, Spain (2003-2005), and Zutitu Ltd. (2005-2006). With a grant from the Oriol Urquijo Foundation, he developed his doctoral dissertation “effects of psychological intervention in the cognitive decline of residentialized elderly people,” published by UMI Dissertation Publishing, Ann Harbor, Michigan, USA. After teaching some courses of maintenance of cognitive functions and laugh therapy to elderly people in Vitoria, Spain (2007-2008), he worked as a researcher at Fundacion INGEMA (Instituto Gerontologico Matia [Matia Gerontological Institute]; 2008-2012) in many projects related to aging and disabilities. He is the author and coauthor of many papers and articles related with aging and implementation of technological aids for older people. In 2010, he published two books, The Ageing Process: A Comprehensive Perspective and Memory Gym: A Goal-Based Cognitive Stimulation Program for Older People, published by Deusto Publicaciones (Bilbao, Spain). He is codirector of two doctoral dissertations about cognitive reserve and behavioral disorders in dementia. Currently, he works at the R+D+I Department of Nesplora, providing his knowledge and expertise on cognitive functioning.

Eduardo Cueto, PhD, is a doctor in psychology and cathedratic of psychometrics at the University of Oviedo (Spain). He started his teacher and research career in 1977 as an assistant professor in the Department of Experimental Psychology at the Universidad Complutense of Madrid (Spain). He was lecturer at this university until 1995. Since then, he started working at the University of Oviedo. He develops different research lines in psychometrics, psychological evaluation, and epidemiology and prevention of behavioral risks. He has participated in several research projects, always with an expert view of items analysis and psychometric properties on the construction and validation of different scales, both for research and clinical purposes. He is a national reference in psychometrics and statistics. He usually cooperates in the elaboration and determination of psychometrical properties of the assessment tools developed at Nesplora and provides his knowl-edge in all the validation processes held by the R+D+I team.



Iriarte et al. 27

Paula Irazustabarrena, MA, graduated in pedagogy and psy-chopedagogy and has a master’s degree in educational and psy-chological intervention at the University of Navarra (Spain). She has a high knowledge about learning difficulties and developmen-tal disorders as well as about management and orientation of cognitive and memory, learning, and affective and social pro-cesses. She has implemented several psychological strategies and intervention programs, and has a high knowledge about ADHD. At Nesplora, she develops research and data collection and valida-tion tasks, and provides her wide expertise on learning processes to all the running and novel projects of Nesplora.

Flavio Banterla, Dipl-Ing, is an informatics engineer. He obtained the advanced studies diploma (DEA in Spanish) on informatics engi-neering from the University of the Basque Country (Spain) in 2005. He is an expert in pattern recognition and classification, artificial

intelligence, machine learning, three-dimensional visualization, and computer vision. He is manager and cofounder of Nesplora.

Gema Climent, MSc, graduated in psychology, has a master’s degree in clinical neuropsychology, and post-graduated in child neuropsychology. She has more than 10 years experience treating patients with brain injury as well as a wide experience in the implementation of programs that demand an extensive knowledge of cognitive functioning. She is devoted to the cooperation with other professionals of neuropsychology and psychology to develop projects of innovative technologies grounded on a solid evidence-based theoretical framework, for the application of diag-nosis and treatment. She has also high IT skills that have facili-tated her ability to connect technologies and neuroscience, and has developed clinical and research work in different settings. She is R+D+I department manager and cofounder of Nesplora.



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